The effect of mainland dynamics on data and parameter estimates in island biogeography

Understanding macroevolution on islands requires knowledge of the closest relatives of island species on the mainland. The evolutionary relationships between island and mainland species can be reconstructed using phylogenies, to which models can be fitted to understand the dynamical processes of colonisation and diversification. But how much information on the mainland is needed to gain insight into macroevolution on islands? Here we first test whether species turnover on the mainland and incomplete mainland sampling leave recognisable signatures in community phylogenetic data. We find predictable phylogenetic patterns: colonisation times become older and the perceived proportion of endemic species increases as mainland turnover and incomplete knowledge increase. We then analyse the influence of these factors on the inference performance of the island biogeography model DAISIE, a whole-island community phylogenetic model that assumes that mainland species do not diversify, and that the mainland is fully sampled in the phylogeny. We find that colonisation and diversification rate are estimated with little bias in the presence of mainland extinction and incomplete sampling. By contrast, the rate of anagenesis is overestimated under high levels of mainland extinction and incomplete sampling, because these increase the perceived level of island endemism. We conclude that community-wide phylogenetic and endemism datasets of island species carry a signature of mainland extinction and sampling. The robustness of parameter estimates suggests that island diversification and colonisation can be studied even with limited knowledge of mainland dynamics.

Histological analysis of thrombi retrieved after acute ischemic stroke from large vessel occlusion: from research to clinical practice

Emergent reperfusion therapies have improved acute ischemic stroke prognosis, but many patients are still bound to bad clinical outcome, probably because of our incomplete knowledge of its pathophysiology. Thanks to mechanical thrombectomy, occluding material is available for histological analysis. Several studies investigated the possible relationship between thrombus composition and clinical, procedural, and radiological variables of acute ischemic stroke. The potential value of thrombus analysis as a tool for clinical practice and research is still not defined, as data from the literature are heterogeneous and sometimes conflicting. We propose a review of the existing literature regarding histological analysis of thrombi in acute ischemic stroke. We classified articles on clot composition according to the clinical variable explored in each study. We first distinguished articles about etiology, procedural, and radiological variables, and then we performed a subclassification for each group. This review could help both in the interpretation of thrombus analysis in clinical practice and in its usage for future research.

Broadband Optical Constants and Nonlinear Properties of SnS2 and SnSe2

SnS2 and SnSe2 have recently been shown to have a wide range of applications in photonic and optoelectronic devices. However, because of incomplete knowledge about their optical characteristics, the use of SnS2 and SnSe2 in optical engineering remains challenging. Here, we addressed this problem by establishing SnS2 and SnSe2 linear and nonlinear optical properties in the broad (300–3300 nm) spectral range. Coupled with the first-principle calculations, our experimental study unveiled the full dielectric tensor of SnS2 and SnSe2. Furthermore, we established that SnS2 is a promising material for visible high refractive index nanophotonics. Meanwhile, SnSe2 demonstrates a stronger nonlinear response compared with SnS2. Our results create a solid ground for current and next-generation SnS2- and SnSe2-based devices.

Case Study of an Outbreak: Resident, Staff, and Community Indicators

Outbreak investigation is not infection control. We present a self-study of factors influencing outcomes inside a single nursing home during the early stage of the outbreak - February to May 2020. We examine 3 sources of influence: Practice / Operations; Local, State & Federal Policies; Uncontrollable operational factors. Outcomes of interest include: mortality and resident / staff health. Data consists of clinical records, review of communications, and interviews with staff present during the critical period. Infection control is different from outbreak investigation. There must be a balance between staff empowerment and adherence to guidelines. In an outbreak, staff need the confidence to make decisions based on incomplete knowledge. The presentation concludes with lessons learned – what worked and what actions need improvement. There are areas requiring further analyses of policy and ethics.

The "Meda" Project: Creation of The Underwater Archaeological Map in Santa Marinella. Prospects for The Reconstruction of the Ancient Landscape

The importance of studying the coasts and the seabed is already known. In any case, the submerged archaeological presences remain today an aspect not yet addressed in a completely systematic way, often remaining a rather incomplete knowledge. The cataloguing of submerged archaeological evidence, through the formation of underwater deposits maps and the study of these, through the contribution of GIS methodologies, fortuitous - to the understanding of their origins and their transformation over time.

Yes, no, maybe, I don’t know: Complexity and application of abstract argumentation with incomplete knowledge

argumentation, as originally defined by Dung, is a model that allows the description of certain information about arguments and relationships between them: in an abstract argumentation framework (AF), the agent knows for sure whether a given argument or attack exists. It means that the absence of an attack between two arguments can be interpreted as “we know that the first argument does not attack the second one”. But the question of uncertainty in abstract argumentation has received much attention in the last years. In this paper, we survey approaches that allow to express information like “There may (or may not) be an attack between these arguments”. We describe the main models that incorporate qualitative uncertainty (or ignorance) in abstract argumentation, as well as some applications of these models. We also highlight some open questions that deserve some attention in the future.

From Mice to Mainframes: Experimental Models for Investigation of the Intracardiac Nervous System

The intracardiac nervous system (IcNS), sometimes referred to as the “little brain” of the heart, is involved in modulating many aspects of cardiac physiology. In recent years our fundamental understanding of autonomic control of the heart has drastically improved, and the IcNS is increasingly being viewed as a therapeutic target in cardiovascular disease. However, investigations of the physiology and specific roles of intracardiac neurons within the neural circuitry mediating cardiac control has been hampered by an incomplete knowledge of the anatomical organisation of the IcNS. A more thorough understanding of the IcNS is hoped to promote the development of new, highly targeted therapies to modulate IcNS activity in cardiovascular disease. In this paper, we first provide an overview of IcNS anatomy and function derived from experiments in mammals. We then provide descriptions of alternate experimental models for investigation of the IcNS, focusing on a non-mammalian model (zebrafish), neuron-cardiomyocyte co-cultures, and computational models to demonstrate how the similarity of the relevant processes in each model can help to further our understanding of the IcNS in health and disease.

Bayesian inference with incomplete knowledge explains perceptual confidence and its deviations from accuracy

In perceptual decisions, subjects infer hidden states of the environment based on noisy sensory information. Here we show that both choice and its associated confidence are explained by a Bayesian framework based on partially observable Markov decision processes (POMDPs). We test our model on monkeys performing a direction-discrimination task with post-decision wagering, demonstrating that the model explains objective accuracy and predicts subjective confidence. Further, we show that the model replicates well-known discrepancies of confidence and accuracy, including the hard-easy effect, opposing effects of stimulus variability on confidence and accuracy, dependence of confidence ratings on simultaneous or sequential reports of choice and confidence, apparent difference between choice and confidence sensitivity, and seemingly disproportionate influence of choice-congruent evidence on confidence. These effects may not be signatures of sub-optimal inference or discrepant computational processes for choice and confidence. Rather, they arise in Bayesian inference with incomplete knowledge of the environment.